prompt on unavailable extension packages

NEWS.md

@@ -12,6 +12,8 @@
 
 * `predict(type = "prob")` will now provide an error if the outcome variable has a level called `"class"` (#720).
 
+* Print methods will now prompt informatively if a needed parsnip extension package is not loaded (#731).
+
 # parsnip 0.2.1
 
 * Fixed a major bug in spark models induced in the previous version (#671).

R/arguments.R

@@ -67,7 +67,8 @@ set_args <- function(object, ...) {
     eng_args = object$eng_args,
     mode = object$mode,
     method = NULL,
-    engine = object$engine
+    engine = object$engine,
+    new = FALSE
   )
 }
 

R/bag_mars.R

@@ -47,7 +47,7 @@ print.bag_mars <- function(x, ...) {
   cat("Bagged MARS Model Specification (", x$mode, ")\n\n", sep = "")
   model_printer(x, ...)
 
-  if (!is.null(x$method$fit$args)) {
+  if (!is.null(x$method$fit$args) && has_loaded_implementation(class(x)[1], x$engine, x$mode)) {
     cat("Model fit template:\n")
     print(show_call(x))
   }

R/bag_tree.R

@@ -51,7 +51,7 @@ print.bag_tree <- function(x, ...) {
   cat("Bagged Decision Tree Model Specification (", x$mode, ")\n\n", sep = "")
   model_printer(x, ...)
 
-  if (!is.null(x$method$fit$args)) {
+  if (!is.null(x$method$fit$args) && has_loaded_implementation(class(x)[1], x$engine, x$mode)) {
     cat("Model fit template:\n")
     print(show_call(x))
   }

R/bart.R

@@ -95,7 +95,7 @@ print.bart <- function(x, ...) {
   cat("BART Model Specification (", x$mode, ")\n\n", sep = "")
   model_printer(x, ...)
 
-  if(!is.null(x$method$fit$args)) {
+  if (!is.null(x$method$fit$args) && has_loaded_implementation(class(x)[1], x$engine, x$mode)) {
     cat("Model fit template:\n")
     print(show_call(x))
   }

R/boost_tree.R

@@ -84,7 +84,7 @@ print.boost_tree <- function(x, ...) {
   cat("Boosted Tree Model Specification (", x$mode, ")\n\n", sep = "")
   model_printer(x, ...)
 
-  if (!is.null(x$method$fit$args)) {
+  if (!is.null(x$method$fit$args) && has_loaded_implementation(class(x)[1], x$engine, x$mode)) {
     cat("Model fit template:\n")
     print(show_call(x))
   }

R/c5_rules.R

@@ -68,7 +68,7 @@ print.C5_rules <- function(x, ...) {
   cat("C5.0 Model Specification (", x$mode, ")\n\n", sep = "")
   model_printer(x, ...)
 
-  if (!is.null(x$method$fit$args)) {
+  if (!is.null(x$method$fit$args) && has_loaded_implementation(class(x)[1], x$engine, x$mode)) {
     cat("Model fit template:\n")
     print(show_call(x))
   }

R/cubist_rules.R

@@ -94,7 +94,7 @@ print.cubist_rules <- function(x, ...) {
   cat("Cubist Model Specification (", x$mode, ")\n\n", sep = "")
   model_printer(x, ...)
 
-  if (!is.null(x$method$fit$args)) {
+  if (!is.null(x$method$fit$args) && has_loaded_implementation(class(x)[1], x$engine, x$mode)) {
     cat("Model fit template:\n")
     print(show_call(x))
   }

R/decision_tree.R

@@ -56,7 +56,7 @@ print.decision_tree <- function(x, ...) {
   cat("Decision Tree Model Specification (", x$mode, ")\n\n", sep = "")
   model_printer(x, ...)
 
-  if (!is.null(x$method$fit$args)) {
+  if (!is.null(x$method$fit$args) && has_loaded_implementation(class(x)[1], x$engine, x$mode)) {
     cat("Model fit template:\n")
     print(show_call(x))
   }

R/discrim_flexible.R

@@ -50,7 +50,7 @@ print.discrim_flexible <- function(x, ...) {
   cat("Flexible Discriminant Model Specification (", x$mode, ")\n\n", sep = "")
   model_printer(x, ...)
 
-  if (!is.null(x$method$fit$args)) {
+  if (!is.null(x$method$fit$args) && has_loaded_implementation(class(x)[1], x$engine, x$mode)) {
     cat("Model fit template:\n")
     print(show_call(x))
   }

R/discrim_linear.R

@@ -52,7 +52,7 @@ print.discrim_linear <- function(x, ...) {
   cat("Linear Discriminant Model Specification (", x$mode, ")\n\n", sep = "")
   model_printer(x, ...)
 
-  if (!is.null(x$method$fit$args)) {
+  if (!is.null(x$method$fit$args) && has_loaded_implementation(class(x)[1], x$engine, x$mode)) {
     cat("Model fit template:\n")
     print(show_call(x))
   }

R/discrim_quad.R

@@ -46,7 +46,7 @@ print.discrim_quad <- function(x, ...) {
   cat("Quadratic Discriminant Model Specification (", x$mode, ")\n\n", sep = "")
   model_printer(x, ...)
 
-  if (!is.null(x$method$fit$args)) {
+  if (!is.null(x$method$fit$args) && has_loaded_implementation(class(x)[1], x$engine, x$mode)) {
     cat("Model fit template:\n")
     print(show_call(x))
   }

R/discrim_regularized.R

@@ -67,7 +67,7 @@ print.discrim_regularized <- function(x, ...) {
   cat("Regularized Discriminant Model Specification (", x$mode, ")\n\n", sep = "")
   model_printer(x, ...)
 
-  if (!is.null(x$method$fit$args)) {
+  if (!is.null(x$method$fit$args) && has_loaded_implementation(class(x)[1], x$engine, x$mode)) {
     cat("Model fit template:\n")
     print(show_call(x))
   }

R/engine_docs.R

@@ -243,7 +243,10 @@ make_engine_list <- function(mod) {
 
 get_default_engine <- function(mod, pkg = "parsnip") {
   cl <- rlang::call2(mod, .ns = pkg)
-  rlang::eval_tidy(cl)$engine
+  suppressMessages(
+    res <- rlang::eval_tidy(cl)$engine
+  )
+  res
 }
 
 #' @export

R/engines.R

@@ -129,7 +129,8 @@ set_engine <- function(object, engine, ...) {
     eng_args = enquos(...),
     mode = object$mode,
     method = NULL,
-    engine = object$engine
+    engine = object$engine,
+    new = FALSE
   )
 }
 

R/gen_additive_mod.R

@@ -55,7 +55,7 @@ print.gen_additive_mod <- function(x, ...) {
   cat("GAM Specification (", x$mode, ")\n\n", sep = "")
   model_printer(x, ...)
 
-  if(!is.null(x$method$fit$args)) {
+  if (!is.null(x$method$fit$args) && has_loaded_implementation(class(x)[1], x$engine, x$mode)) {
     cat("Model fit template:\n")
     print(show_call(x))
   }

R/linear_reg.R

@@ -63,7 +63,7 @@ print.linear_reg <- function(x, ...) {
   cat("Linear Regression Model Specification (", x$mode, ")\n\n", sep = "")
   model_printer(x, ...)
 
-  if (!is.null(x$method$fit$args)) {
+  if (!is.null(x$method$fit$args) && has_loaded_implementation(class(x)[1], x$engine, x$mode)) {
     cat("Model fit template:\n")
     print(show_call(x))
   }

R/logistic_reg.R

@@ -70,7 +70,7 @@ print.logistic_reg <- function(x, ...) {
   cat("Logistic Regression Model Specification (", x$mode, ")\n\n", sep = "")
   model_printer(x, ...)
 
-  if(!is.null(x$method$fit$args)) {
+  if (!is.null(x$method$fit$args) && has_loaded_implementation(class(x)[1], x$engine, x$mode)) {
     cat("Model fit template:\n")
     print(show_call(x))
   }

R/mars.R

@@ -54,7 +54,7 @@ print.mars <- function(x, ...) {
   cat("MARS Model Specification (", x$mode, ")\n\n", sep = "")
   model_printer(x, ...)
 
-  if(!is.null(x$method$fit$args)) {
+  if (!is.null(x$method$fit$args) && has_loaded_implementation(class(x)[1], x$engine, x$mode)) {
     cat("Model fit template:\n")
     print(show_call(x))
   }

R/misc.R

@@ -79,6 +79,72 @@ model_printer <- function(x, ...) {
 is_missing_arg <- function(x)
   identical(x, quote(missing_arg()))
 
+# given a model object, return TRUE if:
+# * the model is supported without extensions
+# * the model needs an extension and it is loaded
+#
+# return FALSE if:
+# * the model needs an extension and it is _not_ loaded
+has_loaded_implementation <- function(spec_, engine_, mode_) {
+  if (isFALSE(mode_ %in% c("regression", "censored regression", "classification"))) {
+    mode_ <- c("regression", "censored regression", "classification")
+  }
+  eng_cond <- if (is.null(engine_)) {TRUE} else {quote(engine == engine_)}
+
+  avail <-
+    get_from_env(spec_) %>%
+    dplyr::filter(mode %in% mode_, !!eng_cond)
+  pars <-
+    utils::read.delim(system.file("models.tsv", package = "parsnip")) %>%
+    dplyr::filter(model == spec_, !!eng_cond, mode %in% mode_, is.na(pkg))
+
+  if (nrow(pars) > 0 || nrow(avail) > 0) {
+    return(TRUE)
+  }
+
+  FALSE
+}
+
+# construct a message informing the user that there are no
+# implementations for the current model spec / mode / engine.
+#
+# if there's a "pre-registered" extension supporting that setup,
+# nudge the user to install/load it.
+prompt_missing_implementation <- function(spec_, engine_, mode_) {
+  avail <-
+    show_engines(spec_) %>%
+    dplyr::filter(mode == mode_, engine == engine_)
+  all <-
+    utils::read.delim(system.file("models.tsv", package = "parsnip")) %>%
+    dplyr::filter(model == spec_, mode == mode_, engine == engine_, !is.na(pkg)) %>%
+    dplyr::select(-model)
+
+  if (identical(mode_, "unknown")) {
+    mode_ <- ""
+  }
+
+  msg <-
+    glue::glue(
+      "parsnip could not locate an implementation for `{spec_}` {mode_} model ",
+      "specifications using the `{engine_}` engine."
+    )
+
+  if (nrow(avail) == 0 && nrow(all) > 0) {
+    msg <-
+      glue::glue_collapse(c(
+        msg,
+        glue::glue_collapse(c(
+          "\nThe parsnip extension package {",
+          cli::col_yellow(all$pkg[[1]]),
+          "} implements support for this specification. \n",
+          "Please install (if needed) and load to continue.\n"
+        ))
+      ))
+  }
+
+  msg
+}
+
 
 #' Print the model call
 #'
@@ -89,18 +155,10 @@ is_missing_arg <- function(x)
 show_call <- function(object) {
   object$method$fit$args <-
     map(object$method$fit$args, convert_arg)
-  if (
-    is.null(object$method$fit$func["pkg"]) ||
-    is.na(object$method$fit$func["pkg"])
-  ) {
-    res <- call2(object$method$fit$func["fun"], !!!object$method$fit$args)
-  } else {
-    res <-
-      call2(object$method$fit$func["fun"],
-            !!!object$method$fit$args,
-            .ns = object$method$fit$func["pkg"])
-  }
-  res
+
+  call2(object$method$fit$func["fun"],
+        !!!object$method$fit$args,
+        .ns = object$method$fit$func["pkg"])
 }
 
 convert_arg <- function(x) {
@@ -110,7 +168,6 @@ convert_arg <- function(x) {
     x
 }
 
-
 levels_from_formula <- function(f, dat) {
   if (inherits(dat, "tbl_spark"))
     res <- NULL
@@ -181,10 +238,14 @@ update_dot_check <- function(...) {
 #' @export
 #' @keywords internal
 #' @rdname add_on_exports
-new_model_spec <- function(cls, args, eng_args, mode, method, engine) {
+new_model_spec <- function(cls, args, eng_args, mode, method, engine, new = TRUE) {
 
   check_spec_mode_engine_val(cls, engine, mode)
 
+  if ((!has_loaded_implementation(cls, engine, mode)) && new) {
+    rlang::inform(prompt_missing_implementation(cls, engine, mode))
+  }
+
   out <- list(args = args, eng_args = eng_args,
               mode = mode, method = method, engine = engine)
   class(out) <- make_classes(cls)

R/mlp.R

@@ -64,7 +64,7 @@ print.mlp <- function(x, ...) {
   cat("Single Layer Neural Network Specification (", x$mode, ")\n\n", sep = "")
   model_printer(x, ...)
 
-  if(!is.null(x$method$fit$args)) {
+  if (!is.null(x$method$fit$args) && has_loaded_implementation(class(x)[1], x$engine, x$mode)) {
     cat("Model fit template:\n")
     print(show_call(x))
   }

R/multinom_reg.R

@@ -70,7 +70,7 @@ print.multinom_reg <- function(x, ...) {
   cat("Multinomial Regression Model Specification (", x$mode, ")\n\n", sep = "")
   model_printer(x, ...)
 
-  if (!is.null(x$method$fit$args)) {
+  if (!is.null(x$method$fit$args) && has_loaded_implementation(class(x)[1], x$engine, x$mode)) {
     cat("Model fit template:\n")
     print(show_call(x))
   }

R/naive_Bayes.R

@@ -49,7 +49,7 @@ print.naive_Bayes <- function(x, ...) {
   cat("Naive Bayes Model Specification (", x$mode, ")\n\n", sep = "")
   model_printer(x, ...)
 
-  if (!is.null(x$method$fit$args)) {
+  if (!is.null(x$method$fit$args) && has_loaded_implementation(class(x)[1], x$engine, x$mode)) {
     cat("Model fit template:\n")
     print(show_call(x))
   }

R/nearest_neighbor.R

@@ -60,7 +60,7 @@ print.nearest_neighbor <- function(x, ...) {
   cat("K-Nearest Neighbor Model Specification (", x$mode, ")\n\n", sep = "")
   model_printer(x, ...)
 
-  if(!is.null(x$method$fit$args)) {
+  if (!is.null(x$method$fit$args) && has_loaded_implementation(class(x)[1], x$engine, x$mode)) {
     cat("Model fit template:\n")
     print(show_call(x))
   }

R/pls.R

@@ -45,7 +45,7 @@ print.pls <- function(x, ...) {
   cat("PLS Model Specification (", x$mode, ")\n\n", sep = "")
   model_printer(x, ...)
 
-  if (!is.null(x$method$fit$args)) {
+  if (!is.null(x$method$fit$args) && has_loaded_implementation(class(x)[1], x$engine, x$mode)) {
     cat("Model fit template:\n")
     print(show_call(x))
   }

R/poisson_reg.R

@@ -56,7 +56,7 @@ print.poisson_reg <- function(x, ...) {
   cat("Poisson Regression Model Specification (", x$mode, ")\n\n", sep = "")
   model_printer(x, ...)
 
-  if (!is.null(x$method$fit$args)) {
+  if (!is.null(x$method$fit$args) && has_loaded_implementation(class(x)[1], x$engine, x$mode)) {
     cat("Model fit template:\n")
     print(show_call(x))
   }

R/proportional_hazards.R

@@ -58,7 +58,7 @@ print.proportional_hazards <- function(x, ...) {
   cat("Proportional Hazards Model Specification (", x$mode, ")\n\n", sep = "")
   model_printer(x, ...)
 
-  if (!is.null(x$method$fit$args)) {
+  if (!is.null(x$method$fit$args) && has_loaded_implementation(class(x)[1], x$engine, x$mode)) {
     cat("Model fit template:\n")
     print(show_call(x))
   }

R/rand_forest.R

@@ -56,7 +56,7 @@ print.rand_forest <- function(x, ...) {
   cat("Random Forest Model Specification (", x$mode, ")\n\n", sep = "")
   model_printer(x, ...)
 
-  if(!is.null(x$method$fit$args)) {
+  if (!is.null(x$method$fit$args) && has_loaded_implementation(class(x)[1], x$engine, x$mode)) {
     cat("Model fit template:\n")
     print(show_call(x))
   }

R/rule_fit.R

@@ -70,7 +70,7 @@ print.rule_fit <- function(x, ...) {
   cat("RuleFit Model Specification (", x$mode, ")\n\n", sep = "")
   model_printer(x, ...)
 
-  if (!is.null(x$method$fit$args)) {
+  if (!is.null(x$method$fit$args) && has_loaded_implementation(class(x)[1], x$engine, x$mode)) {
     cat("Model fit template:\n")
     print(show_call(x))
   }

R/surv_reg.R

@@ -57,7 +57,7 @@ print.surv_reg <- function(x, ...) {
   cat("Parametric Survival Regression Model Specification (", x$mode, ")\n\n", sep = "")
   model_printer(x, ...)
 
-  if(!is.null(x$method$fit$args)) {
+  if (!is.null(x$method$fit$args) && has_loaded_implementation(class(x)[1], x$engine, x$mode)) {
     cat("Model fit template:\n")
     print(show_call(x))
   }

R/survival_reg.R

@@ -51,7 +51,7 @@ print.survival_reg <- function(x, ...) {
   cat("Parametric Survival Regression Model Specification (", x$mode, ")\n\n", sep = "")
   model_printer(x, ...)
 
-  if (!is.null(x$method$fit$args)) {
+  if (!is.null(x$method$fit$args) && has_loaded_implementation(class(x)[1], x$engine, x$mode)) {
     cat("Model fit template:\n")
     print(show_call(x))
   }